Helper Module for Deep Learning.
Module that provides functions to prepare the TCGA-LGG-tif dataset.
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class
pynet.datasets.tcga_lgg_tif.Item(input_path, output_path, metadata_path, height, width)¶ -
property
height¶ Alias for field number 3
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property
input_path¶ Alias for field number 0
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property
metadata_path¶ Alias for field number 2
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property
output_path¶ Alias for field number 1
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property
width¶ Alias for field number 4
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property
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pynet.datasets.tcga_lgg_tif.fetch_tcga_lgg_tif(datasetdir)[source]¶ Fetch/prepare the TCA-LGG-tif dataset for pynet.
The patient average age was 47 with an almost even split between women and men (56 vs. 53, 1 unknown) in our dataset. Histologically, the tumors were divided between oligodendroglioma (47), astrocytoma (33), and oligoastrocytoma (29). Histology of one tumor was unknown. The data included grade II (51) and grade III (58) tumors with grade of one tumor unknown.
- Parameters
datasetdir: str
the dataset destination folder.
- Returns
item: namedtuple
a named tuple containing ‘input_path’, ‘output_path’, ‘metadata_path’, ‘height’ and ‘width’.
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Inspired by AZMIND template.